List of NVIDIA DGX Platform Customers
NVIDIA
2788 San Tomas Expressway,
Santa Clara, 95051, CA,
United States
Santa Clara, 95051, CA,
United States
1 408-486-2000
Manufacturing
36000
$130.5B
Since 2010, our global team of researchers has been studying NVIDIA DGX Platform customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased NVIDIA DGX Platform for AI infrastructure from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using NVIDIA DGX Platform for AI infrastructure include: BMW Group, a Germany based Automotive organisation with 146064 employees and revenues of $163.30 billion, Lockheed Martin, a United States based Aerospace and Defense organisation with 121000 employees and revenues of $71.04 billion, Novo Nordisk, a Denmark based Life Sciences organisation with 78554 employees and revenues of $45.92 billion, MediaTek, a Taiwan based Manufacturing organisation with 21982 employees and revenues of $16.17 billion, E4 Computer Engineering, a Italy based Manufacturing organisation with 83 employees and revenues of $65.0 million and many others.
Contact us if you need a completed and verified list of companies using NVIDIA DGX Platform, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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BMW Group | Automotive | 146064 | $163.3B | Germany | NVIDIA | NVIDIA DGX Platform | AI infrastructure | 2019 | n/a |
In 2019, BMW implemented the NVIDIA DGX Platform as core AI infrastructure for its manufacturing operations in Germany. The NVIDIA DGX Platform is used to generate synthetic data and to train deep learning models that target production quality control, factory optimization, and supply-chain simulations.
Deployment centers on high-performance NVIDIA DGX systems and preconfigured DGX software stacks to support model training and production inference workflows. Functional capabilities include synthetic data generation pipelines, supervised and unsupervised model training, and inference orchestration to drive QA automation and factory optimization models. DGX cluster usage is inferred from the case study to provide scalable GPU pooling and parallel training for production-grade workloads.
Operational scope spans R&D through production model training and inference across BMW Group manufacturing operations in Germany, impacting data science teams, quality assurance, production engineering, and supply-chain planning functions. The implementation positions the NVIDIA DGX Platform as the centralized AI infrastructure for manufacturing model lifecycle management from experimentation to production inference.
Governance and rollout integrated DGX based compute into manufacturing model pipelines and operational QA processes, enabling models to move from lab validation to embedded production use. The case study reports up to an 8x boost in data scientist productivity and significant improvements in QA automation as outcomes of the NVIDIA DGX Platform deployment.
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E4 Computer Engineering | Manufacturing | 83 | $65M | Italy | NVIDIA | NVIDIA DGX Platform | AI infrastructure | 2017 | n/a |
In 2017, E4 Computer Engineering implemented the NVIDIA DGX Platform as a core component of its AI infrastructure to support HPC and AI workloads targeted at Automotive, Medical, and Manufacturing customers in the Italian enterprise market. The deployment was framed to enable internal AI research and engineering functions, aligning the NVIDIA DGX Platform with the company sales focus on senior technical decision makers such as CTOs and Heads of AI.
The implementation centered on on-premises GPU compute nodes based on the NVIDIA DGX Platform integrated with high-performance storage and networking stacks to support large model training and inferencing pipelines. Standard AI infrastructure capabilities were configured, including cluster management and orchestration for distributed training, data ingestion pathways for test and production data, and workload scheduling to optimize GPU utilization across engineering and R&D teams.
Operational scope covered enterprise engagements in Italy and internal product development teams, with integrations explicitly including HPC, storage, networking, and hybrid connectivity to cloud solutions where required. Governance and rollout were coordinated with executive technical stakeholders, using a phased approach to introduce DGX-powered model development workflows into existing engineering processes while aligning procurement and technical scoping with sales pipeline activities.
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Lockheed Martin | Aerospace and Defense | 121000 | $71.0B | United States | NVIDIA | NVIDIA DGX Platform | AI infrastructure | 2021 | n/a |
In 2021, Lockheed Martin implemented the NVIDIA DGX Platform to build an on-prem AI Factory powered by an NVIDIA DGX SuperPOD. The AI Factory consolidated high-performance GPU compute and MLOps under an AI infrastructure deployment supporting enterprise R&D and engineering in the United States.
The NVIDIA DGX Platform was configured to centralize compute orchestration and MLOps capabilities, supporting large-scale LLM training and hosting. Functional capabilities implemented include training pipelines for generative models, persistent model hosting for internal chatbots and coding assistants, and workflows to manage model lifecycle and experiment tracking.
The deployment operated as an on-prem DGX SuperPOD cluster serving R&D and engineering teams across Lockheed Martin, processing over one billion tokens per week for training and inference workloads. The platform was embedded into developer workflows to shorten iteration cycles and to provide a centralized environment for dataset preparation, model training, and inference serving for internal generative-AI use cases.
Governance changes focused on centralizing compute and standardizing MLOps processes to improve developer productivity and operational control, with rollout concentrated on enterprise R&D and engineering functions. The implementation substantially reduced training time and costs and enabled faster developer productivity and processes, according to the source.
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MediaTek | Manufacturing | 21982 | $16.2B | Taiwan | NVIDIA | NVIDIA DGX Platform | AI infrastructure | 2025 | n/a |
In 2025, MediaTek deployed the NVIDIA DGX Platform as an on premises AI factory powered by an NVIDIA DGX SuperPOD to train and deploy its Breeze series very large language models. This implementation positions the NVIDIA DGX Platform as core AI infrastructure for MediaTek, focused on AI R&D and device and edge model optimization in Taiwan.
The deployment concentrates on high-throughput training and inference pipelines to support very large language model development, model iteration workflows, and device-level optimization. Functional capabilities reported include large-scale model training, inference serving, and accelerated R&D workflows that support frequent model retraining and iteration on the Breeze series.
Operationally the DGX SuperPOD cluster is hosted on premises in Taiwan and is used by MediaTek research and engineering teams responsible for AI R&D and device and edge model tuning. The implementation supports both training and deployment workflows, enabling tighter coordination between model development and device optimization efforts across product engineering and research groups.
MediaTek reports tens of billions of tokens processed monthly and large gains in training and inference throughput, with faster inference and higher token throughput enabling accelerated model iteration. The narrative emphasizes the NVIDIA DGX Platform as AI infrastructure that materially changed throughput and iteration cadence for MediaTeks AI R&D and device model optimization efforts.
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Novo Nordisk | Life Sciences | 78554 | $45.9B | Denmark | NVIDIA | NVIDIA DGX Platform | AI infrastructure | 2025 | n/a |
In 2025, Novo Nordisk implemented the NVIDIA DGX Platform as a core AI infrastructure deployment to accelerate drug discovery and early clinical development. The NVIDIA DGX Platform is provisioned via DCAI's Gefion supercomputer and NVIDIA DGX SuperPOD, establishing an AI factory for running generative and agentic AI workloads across Novo Nordisk research teams.
The implementation centers on NVIDIA BioNeMo for generative AI drug design, NVIDIA NIM and NVIDIA NeMo microservices for building customized agentic workflows, and the NVIDIA Omniverse platform for physically accurate simulation environments. These components are configured to support single cell modeling, molecule generation with drug like properties, and biomedical large language model development using Novo Nordisk's global scientific literature, reflecting typical AI infrastructure modules for model training, inference, and simulation.
Operational integration ties the NVIDIA DGX Platform to DCAI's Gefion resources, enabling high performance compute orchestration and data access for Novo Nordisk R and D and early research and clinical development functions. The scope includes Danish supercomputing resources and Novo Nordisk’s global research footprint, with workflows designed to run large scale experiments, model training pipelines, and agentic workflows that interact with simulation and microservice stacks.
Governance and workflow restructuring emphasize model curation, secure data access for biomedical text and experimental datasets, and experiment orchestration inside the AI factory concept. Novo Nordisk and NVIDIA state the collaboration will build customized models and agents to aid scientists, and that Gefion and the NVIDIA DGX Platform will allow researchers to run experiments at an unprecedented scale to support faster pharmaceutical development.
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Buyer Intent: Companies Evaluating NVIDIA DGX Platform
ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating NVIDIA DGX Platform. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating NVIDIA DGX Platform for AI infrastructure include:
- H Partners Management, a United States based Banking and Financial Services organization with 10 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated |
|---|---|---|---|---|---|---|
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H Partners Management | Banking and Financial Services | 10 | $1M | United States | 2026-04-02 |
FAQ - APPS RUN THE WORLD NVIDIA DGX Platform Coverage
NVIDIA DGX Platform is a AI infrastructure solution from NVIDIA.
Companies worldwide use NVIDIA DGX Platform, from small firms to large enterprises across 21+ industries.
Organizations such as BMW Group, Lockheed Martin, Novo Nordisk, MediaTek and E4 Computer Engineering are recorded users of
NVIDIA DGX Platform for AI infrastructure.
Companies using NVIDIA DGX Platform are most concentrated in Automotive, Aerospace and Defense and Life Sciences, with adoption spanning over 21 industries.
Companies using NVIDIA DGX Platform are most concentrated in Germany, United States and Denmark, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of NVIDIA DGX Platform across Americas, EMEA, and APAC.
Companies using NVIDIA DGX Platform range from small businesses with 0-100 employees - 20%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 0%, and global enterprises with 10,000+ employees - 80%.
Customers of NVIDIA DGX Platform include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.
Contact APPS RUN THE WORLD to access the full verified NVIDIA DGX Platform customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of AI infrastructure.